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Dehghan E, Le Y, Lee J, et al. CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION. Proc IEEE Int Symp Biomed Imaging. 2016;2016:625-628doi: 10.1109/ISBI.2016.7493345.
Dehghan, E., Le, Y., Lee, J., Song, D. Y., Fichtinger, G., & Prince, J. L. (2016). CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION. Proceedings. IEEE International Symposium on Biomedical Imaging, 2016625-628. https://doi.org/10.1109/ISBI.2016.7493345
Dehghan, Ehsan, et al. "CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2016 (2016): 625-628. doi: https://doi.org/10.1109/ISBI.2016.7493345
Dehghan E, Le Y, Lee J, Song DY, Fichtinger G, Prince JL. CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:625-628. doi: 10.1109/ISBI.2016.7493345. Epub 2016 Jun 16. PMID: 28890754; PMCID: PMC5589189.
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Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:625-628. doi: 10.1109/ISBI.2016.7493345. Epub 2016 Jun 16.

CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION.

Proceedings. IEEE International Symposium on Biomedical Imaging

Ehsan Dehghan, Yi Le, Junghoon Lee, Daniel Y Song, Gabor Fichtinger, Jerry L Prince

Affiliations

  1. IBM Research, San Jose, CA, USA.
  2. Indiana University, Indianapolis, IN, USA.
  3. Johns Hopkins University, Baltimore, MD, USA.
  4. Queen's University, Kingston, ON, Canada.

PMID: 28890754 PMCID: PMC5589189 DOI: 10.1109/ISBI.2016.7493345

Abstract

Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a need for manual initialization. Our registration method employs a point-to-volume registration scheme during which localized seeds in the CT images, produced by commercial treatment planning systems as part of the standard of care, are rigidly registered to preprocessed MRI images. We tested our algorithm on ten patient data sets and achieved an overall registration error of 1.6 ± 0.8 mm with a running time of less than 20s. With high registration accuracy and computational speed, and no need for manual intervention, our method has the potential to be employed in clinical applications.

Keywords: CT; MRI; Multi-Modality Registration; Prostate Brachytherapy

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